Principal Software Engineer

Responsibilities

• Understand customer business needs and actively participate in designing products and value ‑ added AI, GenAI, and agentic AI services.
• Ensure timely delivery and excellent engineering quality across all AI and software deliverables.
• Define AI architecture, coding standards, and best practices for ML, LLM, RAG, and agentic AI systems.
• Architect and implement advanced AI/ML models for NLP, computer vision, predictive analytics, generative AI, and multi ‑ agent workflows.
• Design distributed, scalable, and high ‑ performance AI systems optimized for reliability and enterprise workloads.
• Oversee MLOps & Deployment activities including model deployment, monitoring, observability, and lifecycle management across cloud and on ‑ prem environments.
• Review requirements, design, and code; conduct technical workshops and drive architectural alignment across teams.
• Mentor, support, and motivate engineering teams to achieve technical excellence in AI/ML, Generative AI, and Agentic AI implementations.
• Collaborate with product and business teams to align AI initiatives with organizational goals and strategic roadmap.
• Act as a subject matter expert for AI/ML, GenAI, and agentic AI domains—adopting and integrating the latest frameworks, tools, and technologies.
• Work with QA leads to ensure engineering quality, performance, and release readiness for AI ‑ driven components.
• Evaluate emerging AI, GenAI, and agentic AI technologies and lead adoption of cutting ‑ edge frameworks, including responsible AI practices and guardrails for safe usage.
• End to end Product & feature development including effort estimations, design, coding, testing and automation
• Understand customer’s business needs, product non-functional requirements and drives estimation of development tasks
• Designs, develops, tests, documents and drives the implementation of moderately to highly complex systems, considering impact on the broader landscape, systems and components.
• Ensures timely delivery and excellent quality of the deliverables for the product
• Able to represent the product team externally and /or other external technology body with confidence
• Acts as subject matter expert for the domain, technologies and also able to adapt latest technologies, frameworks and tools quickly
• Reviewing requirements, design, code, use cases, unit tests within team
• Able to resolve technical problems and help team members with technical challenges
• H elp assess team / engineering skills & capabilities and mentor, motivate team members for technical excellence
• The ability to work in global environment, partner effectively with cross-functional teams, and manage multiple priorities and deliverables concurrently
• Collaborates with senior members of development departments to share experiences and knowledge and to identify ways to simplify and integrate products

Required Qualifications

• 13+ years of software engineering experience with at least 7+ years in AI/ML development, including generative AI and agentic AI systems.
• Full time Bachelor and/or master’s degree in engineering with a minimum of 60% grade
• Strong programming proficiency in Python with expertise in enterprise ‑ grade AI/ML and LLM applications.
• Deep experience with ML frameworks—TensorFlow, PyTorch, scikit ‑ learn, Keras — and modern GenAI/agentic AI frameworks such as Hugging Face, LangChain, LangGraph, or AutoGen.
• Proficiency in Machine Learning, Deep Learning, NLP, Generative AI, RAG architecture, vector search, and multi ‑ agent workflows.
• Experience developing, deploying, optimizing, and scaling AI/ML, LLM, and agentic AI models across cloud and on premise environments.
• Expertise in data engineering, feature engineering, embedding pipelines, and large ‑ scale data processing.
• Hands ‑ on experience with MLOps tools — Docker, Kubernetes, CI/CD, MLflow — and cloud platforms (AWS/GCP/Azure).
• Demonstrated experience leading and executing customer‑facing AI solutions, including solution design, model development, deployment, and post‑production optimization.
• Demonstrated ability and experience in the entire product development cycle: from requirements, effort estimation, design, implementation, test and to deployment and production support
• Strong problem-solving skills and the ability to think outside the box Preferred Qualifications
• Experience building enterprise AI platforms
• Experience in delivering scalable and high-performance services and applications with excellent quality
• Experience with LLMs, prompt engineering, and retrieval-augmented generation (RAG) based system.
• Knowledge of GPU optimization, ONNX, TensorRT, and model compression techniques.
• Exposure to enterprise-grade AI deployments and compliance frameworks.
• Experience with advanced topics like reinforcement learning, generative AI, and multimodal systems.
• Publications, patents, or open‑source contributions in AI/ML
• Experience leading AI transformations in large organizations

Company